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Broad learning through fusions = an ...

Zhang, Jiawei.

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Broad learning through fusions = an application on social networks /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Broad learning through fusions/ by Jiawei Zhang, Philip S. Yu.
其他題名:	an application on social networks /
作者:	Zhang, Jiawei.
其他作者:	Yu, Philip S.
出版者:	Cham :Springer International Publishing : : 2019.,
面頁冊數:	xv, 419 p. :ill., digital ;24 cm.
內容註:	1 Broad Learning Introduction -- 2 Machine Learning Overview -- 3 Social Network Overview -- 4 Supervised Network Alignment -- 5 Unsupervised Network Alignment -- 6 Semi-supervised Network Alignment -- 7 Link Prediction -- 8 Community Detection -- 9 Information Diffusion -- 10 Viral Marketing -- 11 Network Embedding -- 12 Frontier and Future Directions -- References.
Contained By:	Springer eBooks
標題:	Data mining. -
電子資源:	https://doi.org/10.1007/978-3-030-12528-8
ISBN:	9783030125288

Broad learning through fusions = an application on social networks /
Zhang, Jiawei.

Broad learning through fusionsan application on social networks /[electronic resource] :by Jiawei Zhang, Philip S. Yu. - Cham :Springer International Publishing :2019. - xv, 419 p. :ill., digital ;24 cm.

1 Broad Learning Introduction -- 2 Machine Learning Overview -- 3 Social Network Overview -- 4 Supervised Network Alignment -- 5 Unsupervised Network Alignment -- 6 Semi-supervised Network Alignment -- 7 Link Prediction -- 8 Community Detection -- 9 Information Diffusion -- 10 Viral Marketing -- 11 Network Embedding -- 12 Frontier and Future Directions -- References.

This book offers a clear and comprehensive introduction to broad learning, one of the novel learning problems studied in data mining and machine learning. Broad learning aims at fusing multiple large-scale information sources of diverse varieties together, and carrying out synergistic data mining tasks across these fused sources in one unified analytic. This book takes online social networks as an application example to introduce the latest alignment and knowledge discovery algorithms. Besides the overview of broad learning, machine learning and social network basics, specific topics covered in this book include network alignment, link prediction, community detection, information diffusion, viral marketing, and network embedding.

ISBN: 9783030125288

Standard No.: 10.1007/978-3-030-12528-8doiSubjects--Topical Terms:

562972
Data mining.

LC Class. No.: QA76.9.D343 / Z43 2019

Dewey Class. No.: 006.312

Broad learning through fusions = an application on social networks /
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520 $a This book offers a clear and comprehensive introduction to broad learning, one of the novel learning problems studied in data mining and machine learning. Broad learning aims at fusing multiple large-scale information sources of diverse varieties together, and carrying out synergistic data mining tasks across these fused sources in one unified analytic. This book takes online social networks as an application example to introduce the latest alignment and knowledge discovery algorithms. Besides the overview of broad learning, machine learning and social network basics, specific topics covered in this book include network alignment, link prediction, community detection, information diffusion, viral marketing, and network embedding.
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